Nov 20, 2023 · In this paper, a novel extended form of multivariate variational mode decomposition (MVMD) method to multigroup data named as grouped MVMD (GMVMD) is proposed.
Abstract— Objective: In this paper, a novel extended form of multivariate variational mode decomposition. (MVMD) method to multigroup data named as grouped.
The effectiveness and superiority of the algorithm are demonstrated on a series of experiments. The utility of GMVMD is verified by grouping real-world ...
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This study proposes variational mode decomposition (VMD) of EEG before feature extraction along with machine learning models.
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This work proposes a novel methodology for feature extraction and classification of motor imagery electroencephalogram signals.
It is a non-parametric technique, which compares the medians of two or more independent groups (Clark et al., 2023). It is essentially a rank-based test.
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A general decomposition form for multichannel multicomponent signals is formulated based on the instantaneous linear mixing model.
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Jul 10, 2019 · Grouped Multivariate Variational Mode Decomposition With Application to EEG Analysis · Jiawei JianDuanpo Wu +4 authors. Shuchang Zhang. Medicine ...
In this paper, a generic extension of variational mode decomposition (VMD) algorithm for multivariate or multichannel data sets is presented.
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May 1, 2023 · Highlights •A novel method for feature extraction of Motor Imagery EEG signals is developed.•The method is based on Multivariate Variational ...
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